Computational protocol: Genomic analysis and clinical management of adolescent cutaneous melanoma

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Protocol publication

[…] DNA from a metastatic cutaneous deposit and whole blood DNA from the index 15‐year‐old patient were genome sequenced on the Illumina X10 platform (Table ). Whole‐genome‐sequenced reads were aligned against the human reference genome (GRCh37) using the Burrows–Wheeler Aligner (Li and Durbin, ; Table ). We used a somatic caller merging approach to identify somatic variants selecting only those detected using four or more algorithms for further analysis (Rashid et al., ). These calls were further filtered for germline polymorphic variants using the 1000 Genomes Project (Auton et al., ), and other standard quality filters were also applied (e.g. depth of coverage ≥10, read mapping quality ≥15). Small insertions and deletions were identified using Scalpel (Narzisi et al., ). Randomly selected candidate variants were validated by capillary sequencing. Large somatic copy number aberrations were detected using the Batternberg algorithm. Somatic variants from a series of 13 ‘conventional’ paediatric melanomas described by Lu et al. () (so‐called due to their shared clinical and histological features typical of adult cutaneous melanoma) and for whom genome sequencing data were available were used for a comparative analysis. Exome sequencing data from a further 275 adult cutaneous melanomas were downloaded from The Cancer Genome Atlas and used for comparison with adult‐onset disease (Table ). [...] Germline DNA from the peripheral blood of five children with resected primary melanoma was whole‐genome‐sequenced on the Illumina HiSeq2500 platform (Tables and ). These sequences, and that of the index case, were combined with whole‐genome and whole‐exome sequences from a collection of 18 children sequenced at St Jude Children's Hospital (Lu et al., ) comprising 13 children from the ‘conventional’ melanoma cohort described above and five from the other histological subgroups described therein (Table ). Germline variants were called using samtools mpileup (Li et al., ) and bcftools (Narasimhan et al., ). These variants were annotated for consequence using Ensembl Variant Effect Predictor (McLaren et al., ) and filtered for non‐synonymous variants. They were then further restricted to those variants known to be rare (allele frequency < 10−3) by comparison with the Exome Aggregation Consortium (ExAc) data set (Lek et al., ) or that were private to a single child. For details, see Table . […]

Pipeline specifications

Software tools BWA, Scalpel, SAMtools, bcftools, VEP
Databases TCGA Data Portal
Application WES analysis
Organisms Homo sapiens
Diseases Melanoma, Neoplasms